# US 12,178,589 B2 · System and method for generating a sensorial stimulus > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,178,589 B2 - Document ID: US12178589B2 - Status: Granted - Kind: B2 - Application number: 16/648,346 - Filed: 2018-09-18 - Published: 2020-07-09 - Granted: 2024-12-31 - Earliest claimed: 2017-09-18 - Assignees: Cyrebro Technologies - Applicants: Cyrebro Technologies - Inventors: Quentin Barthelemy; Louis Mayaud - Web page: https://patentgrep.com/patent/US12178589B2 ## CPC - A61B 5/375: using biofeedback - A61B 5/374: Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves - A61B 5/377: using evoked responses - A61B 5/7203: {for noise prevention, reduction or removal} - A61B 5/7257: {using Fourier transforms} - A61B 5/7405: {using sound} - A61B 5/743: {Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots} - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - A61B 2505/09: Rehabilitation or training - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract The present invention relates to a method for generating a sensorial stimulus using electroencephalographic data acquired from a subject, the method comprising the following steps: receiving electroencephalographic data comprising at least two electroencephalographic signals measured simultaneously from at least two electroencephalogram channels; calculating an alpha phase neuromarker on consecutive epochs of the electroencephalographic data, the alpha phase neuromarker being representative of at least the phase coherence between alpha waves recorded from the at least two electroencephalogram channels; and generating a sensorial stimulus representing alpha phase neuromarker using an output generator. ## Claims ### Claim 1 A computer-implemented method for training a subject to reinforce self-modulation of pain pathways using electroencephalographic data acquired from a brain of the subject, the method comprising the following steps: a) receiving the electroencephalographic data comprising at least two electroencephalographic signals measured simultaneously from at least two electroencephalogram channels; b) filtering the at least two electroencephalographic signals with a band-pass filter that only passes alpha waves; c) computing an averaged signal of the at least two filtered electroencephalographic signals; d) computing an alpha phase synchrony neuromarker as a Frobenius squared norm a of the averaged signal on a first temporal window; and e) generating a sensorial stimulus representing a numerical value of the alpha phase synchrony neuromarker, wherein said sensorial stimulus is selected from the group consisting of: visual stimulus and auditory stimulus; f) training the subject to reinforce self-modulation of pain pathways with the generated sensorial stimulus, by reporting said sensorial stimulus to the subject using an output generator, said output generator being selected among: lights, LEDS, a screen, a smartphone, a computer monitor, a television, or a head-mounted display. ### Claim 2 (depends on 1) The computer-implemented method for training, according to claim 1, wherein computing the alpha phase synchrony neuromarker as the Frobenius squared norm a of the averaged signal on the first temporal window is followed by: a) computing a parameter p as a global field power of the averaged signal on a second temporal window, wherein said second temporal window corresponds to the first temporal window on; and b) normalizing the alpha phase synchrony neuromarker by the global field power of the averaged signal. ### Claim 3 (depends on 1) The computer-implemented method according to claim 1, wherein computing the averaged signal of the at least two filtered electroencephalographic signals, is preceded by removing noise and artefact from the at least two electroencephalographic signals. ### Claim 4 (depends on 1) The computer-implemented method according to claim 1, wherein said sensorial stimulus representing the alpha phase synchrony neuromarker is communicated to the subject. ### Claim 5 (depends on 1) The computer-implemented method according to claim 1, wherein said sensorial stimulus is communicated to the subject in real time. ### Claim 6 (depends on 1) The computer-implemented method according to claim 1, wherein, when said sensorial stimulus is the visual stimulus, the alpha phase synchrony neuromarker value is represented in relation to a reference state. ### Claim 7 (depends on 6) The computer-implemented method according to claim 6, wherein the reference state is defined as one of the following: the alpha phase synchrony neuromarker value obtained by the subject at the beginning of each training session, or the alpha phase synchrony neuromarker value obtained, when the subject is doing a certain task. ### Claim 8 (depends on 6) The computer-implemented method according to claim 6, wherein the reference state is defined as an average alpha phase synchrony neuromarker value obtained from a representative population, said representative population not including the subject who is undergoing a self-paced training session to reinforce self-modulation of pain pathways. ### Claim 9 (depends on 6) The computer-implemented method according to claim 6, wherein the reference state is defined as the alpha phase synchrony neuromarker value obtained by the subject at the beginning of a self-paced training session to reinforce self-modulation of pain pathways. ### Claim 10 (depends on 1) The computer-implemented method according to claim 1, wherein the alpha phase synchrony neuromarker value for the subject is realized through a learning process. ### Claim 11 (depends on 10) The computer-implemented method according to claim 10, wherein the learning process is implemented according to operand conditioning. ### Claim 12 (depends on 11) The computer-implemented method according to claim 11, wherein the learning process comprises rewarding the subject with a positive stimulus when the alpha phase synchrony neuromarker is improved. ### Claim 13 (depends on 12) The computer-implemented method according to claim 12, wherein the learning process further comprises punishing the subject by removing the positive stimulus when the alpha phase synchrony neuromarker is deteriorated. ### Claim 14 (depends on 11) The computer-implemented method according to claim 11, wherein the learning process comprises punishing the subject with a negative stimulus when the alpha phase synchrony neuromarker is deteriorated. ### Claim 15 (depends on 14) The computer-implemented method according to claim 14, wherein the learning process further comprises rewarding the subject by removing the negative stimulus when the alpha phase synchrony neuromarker is improved. ### Claim 16 (depends on 10) The computer-implemented method according to claim 10, wherein the learning process is implemented according to a self-control process consisting in giving the subject a continuous real time representation of the alpha phase synchrony neuromarker in order to allow said subject to gain control and modify the alpha phase synchrony neuromarker to a desired state. ### Claim 17 (depends on 1) The computer-implemented method according to claim 1, further comprising filtering the at least two electroencephalographic signals to remove ocular artefacts. ### Claim 18 A system for training a subject to reinforce self-modulation of pain pathways, the system comprising: an acquisition set-up for acquiring at least two electroencephalographic signals from the subject; a data processing system for carrying out a method comprising: a) receiving the electroencephalographic data comprising at least two electroencephalographic signals measured simultaneously from at least two electroencephalogram channels; b) filtering the at least two electroencephalographic signals with a band-pass filter that only passes alpha waves; c) computing an averaged signal of the at least two filtered electroencephalographic signals; d) computing an alpha phase synchrony neuromarker as a Frobenius squared norm a of the averaged signal on a temporal window; and e) generating a sensorial stimulus representing the alpha phase synchrony neuromarker; and an output generator, by which the data processing system generates the sensorial stimulus, which reports to the subject said sensorial stimulus representing a numerical value of the alpha phase synchrony neuromarker, wherein said sensorial stimulus is selected from the group consisting of: visual stimulus and auditory stimulus, said output generator being selected among: lights, LEDS, a screen, a smartphone, a computer monitor, a television, or a head-mounted display. ### Claim 19 A non-transitory computer-readable storage medium comprising instructions which, when the program is executed by a computer, cause the computer to carry out a computer-implemented method for training a subject to reinforce self-modulation of pain pathways using electroencephalographic data acquired from the brain of said subject, said method comprising: a) receiving the electroencephalographic data comprising at least two electroencephalographic signals measured simultaneously from at least two electroencephalogram channels; b) filtering the at least two electroencephalographic signals with a band-pass filter that only passes alpha waves; c) computing an averaged signal of the at least two filtered electroencephalographic signals; d) computing an alpha phase synchrony neuromarker as a Frobenius squared norm a of the averaged signal on a temporal window; e) generating a sensorial stimulus representing the alpha phase synchrony neuromarker, wherein said sensorial stimulus is selected from the group consisting of: visual stimulus and auditory stimulus; and f) training the subject to reinforce self-modulation of pain pathways with the generated sensorial stimulus, by reporting said sensorial stimulus to the subject using an output generator, said output generator being selected among: lights, LEDS, a screen, a smartphone, a computer monitor, a television, or a head-mounted display.